In recent years, mobile phones having the digital camera function have been widely used, and this digital camera function is used in a variety of ways; for example, photographed images are viewed on the screen of a mobile phone, transferred to computer apparatuses such as a personal computer, or output as printed photographs. In this case, an image photographed by a digital camera is sometimes not suitable as a viewing image due to an improper exposure adjustment when the photograph was taken and, in such a case, the image correction device provided in the mobile phone, computer apparatus, or printer is used for image correction, such as color correction or gradation correction.
The amount of image correction for color correction or gradation correction must be set to the optimum value according to the image, and this optimum value depends on the content of an image or on the preference of a person who views the photograph. Therefore, the ideal correction of images requires the user to manually adjust the correction amounts of images, once for each image, meaning that the manual correction of a large number of images requires vast amounts of manpower. To solve this problem, a method for automatically controlling the image correction on a device is proposed. For example, Non-Patent Document 1 given below proposes an automatic image correction method based on histogram analysis.
However, the image correction method described above, which cannot recognize objects, such as a portrait (photograph of a person), landscape, flower, and night scene, and classify them into respective categories, sometimes corrects images too much depending upon the scene. For example, the color saturation of a portrait is enhanced too much to make the skin color appear redder than it should be. To solve this problem, a method is proposed recently to dynamically change the correction amount of an image by recognizing the scene. For example, Patent Documents 1 and 2 given below disclose a method for recognizing the face area in an image, computing the correction amount suitable for the portrait based on the color distribution analysis of the part, and correcting the image according to the computed correction amount.
In the method described above, though the scene recognition processing is performed usually by computing the feature value of the edges and colors of an input image and, after that, performing the pattern recognition processing based on the computed feature value, the erroneous recognition probability of the pattern recognition processing is not zero. However, because the image correction method described in Patent Documents 1 and 2 do not take into consideration a scene recognition error, there occurs a problem that a scene recognition error, if generated, would lead to a correction amount error and, as a result, image quality degradation.
In addition, the object included in a photographed image is not always one object but, in many cases, a mixture of two or more objects. For example, the image includes persons and grass, persons and flowers, or persons and night scenes. When multiple objects are mixed, correction made to one object may adversely affect the image of other objects.
To solve the problem with a mixture of multiple objects, Patent Document 3 given below discloses a method for creating multiple correction images, one for each of multiple photographed objects, and combining the multiple corrected images according to the positions of the objects. The problem with this method is that the creation of multiple correction images requires a large amount of working memory and therefore increases the processing cost. In addition, because the erroneous recognition of an object is not taken into consideration, an erroneous recognition, if generated, would lead to image quality degradation in the same way as in the methods described above.
Patent Document 1:
    Japanese Patent Kokai Publication No. JP-A-11-283025Patent Document 2:    Japanese Patent Kokai Publication No. JP-P2000-182043APatent Document 3:    Japanese Patent Kokai Publication No. JP-A-11-205583Non-Patent Document 1:    A. Inoue and J. Tajima, “Adaptive Quality Improvement Method for Color Images,” Proc. of SPIE, Vol. 2179, pp. 429-439, 1994.